A novel H∞ control for T-S fuzzy systems with transform matching membership functions

被引:1
|
作者
Zhang, Zhenxing [1 ,2 ,3 ]
Dong, Jiuxiang [1 ,2 ,3 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
[3] Northeastern Univ, Key Lab Vibrat & Control Aeroprop Syst, Minist Educ China, Shenyang, Liaoning, Peoples R China
基金
中国国家自然科学基金;
关键词
Takagi-Sugeno (T -S) fuzzy systems; Robust H 0; 0; control; Membership functions (MFs) online optimization; Dynamical transform; matching parameters; NON-PDC CONTROL; STABILIZATION CRITERIA; STABILITY ANALYSIS; TRACKING CONTROL; DESIGN; FAULT; ROBUST; ALGORITHM; SEARCH;
D O I
10.1016/j.fss.2023.108582
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
This article studies 7-L0,0 optimization issue of Takagi-Sugeno (T-S) fuzzy systems with an improved transform matching membership functions (MFs) approach. Different from existing transform matching MFs control method, a polynomial disassembling strategy is first proposed for T-S fuzzy systems. Then, combining with parameterized linear matrix inequality (LMI) technique which can remove the inequality constraints between the MFs in systems and fuzzy controllers, sufficient conditions are presented to maintain asymptotic stability and desired 7-L0,0 performance for studied plants. Afterwards, a novel MFs online optimization algorithm is proposed for the first time to automatically adjust the values of scaling and bias parameters so as to realize better 7-L0,0 performance. In contrast to the traditional control using improved matching MFs, the practical behavior of disturbance attenuation index is reduced efficiently. Additionally, the proposed MFs online optimization algorithm is capable of sustaining the desired 7-L0,0 performance when the disturbance channels exist modeling errors, i.e., the practical disturbance attenuation index & gamma; is still less than the preset value. For guaranteeing the convergence of cost function, sufficient condition is obtained based upon Lyapunov stability theory. Finally, two demonstrative simulations are presented to confirm the advantages and benefits of the novel MFs online optimization control strategy.& COPY; 2023 Elsevier B.V. All rights reserved.
引用
收藏
页数:23
相关论文
共 50 条
  • [1] A Novel H∞ Control for T-S Fuzzy Systems With Membership Functions Online Optimization Learning
    Zhang, Zhenxing
    Dong, Jiuxiang
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2022, 30 (04) : 1129 - 1138
  • [2] Optimal Containment Control for T-S Fuzzy MASs Using Improved Transform Matching Membership Functions
    Zhang, Zhenxing
    Dong, Jiuxiang
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2024,
  • [3] A novel polynomial membership functions based control method for T-S fuzzy systems
    Xie, Wen-Bo
    Zhang, Jian
    Li, Yi-Fan
    Palhares, Reinaldo M.
    ISA TRANSACTIONS, 2022, 129 : 192 - 203
  • [5] Membership Functions Integration Approach for State Feedback Control of T-S Fuzzy Systems
    Xie, Wen-Bo
    Xu, Bo-Lin
    Peng, Chen
    Nguyen, Anh-Tu
    INTERNATIONAL JOURNAL OF FUZZY SYSTEMS, 2022, 24 (06) : 2931 - 2945
  • [6] Membership Functions Integration Approach for State Feedback Control of T-S Fuzzy Systems
    Wen-Bo Xie
    Bo-Lin Xu
    Chen Peng
    Anh-Tu Nguyen
    International Journal of Fuzzy Systems, 2022, 24 : 2931 - 2945
  • [7] Stability Analysis for T-S Fuzzy Control Systems with Linear Interpolations into Membership Functions
    Wang, Peng
    Li, Ning
    Li, Shaoyuan
    2012 12TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS & VISION (ICARCV), 2012, : 1749 - 1754
  • [8] H∞ Control Design for Network-based T-S Fuzzy Systems with Asynchronous Constraints on Membership Functions
    Zhang, Dawei
    Han, Qing-Long
    IECON 2011: 37TH ANNUAL CONFERENCE ON IEEE INDUSTRIAL ELECTRONICS SOCIETY, 2011, : 2584 - 2589
  • [9] Fault Detection for T-S Fuzzy Systems With Unknown Membership Functions
    Li, Xiao-Jian
    Yang, Guang-Hong
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2014, 22 (01) : 139 - 152
  • [10] H∞ control for T-S fuzzy descriptor systems
    Liu, Xiao-Dong
    Zhang, Qing-Ling
    Wang, Yan
    Dongbei Daxue Xuebao/Journal of Northeastern University, 2002, 23 (05): : 428 - 431